** descriptive statistics of observational analysis (table 1)

su populism1 nostalgia1 income1 female metropol education1 age religious alevi1 kurdish eusup trust lifsat demsat econsat akp hdp chp mhp [aweight=total_weight]

** observational analysis ols regression with beta coefficients (table 2)


eststo clear
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust [pweight=total_weight], b
eststo model1
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust akp[pweight=total_weight], b
eststo model2
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust chp[pweight=total_weight], b
eststo model3
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust mhp[pweight=total_weight], b
eststo model4
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust hdp[pweight=total_weight], b
eststo model5
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat [pweight=total_weight], b
eststo model6
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat akp [pweight=total_weight], b
eststo model7
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat chp [pweight=total_weight], b
eststo model8
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat mhp [pweight=total_weight], b
eststo model9
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat hdp [pweight=total_weight], b
eststo model10
esttab model1 model2 model3 model4 model5 model6 model7 model8 model9 model10 using popdv.rtf, beta r2 star(+ 0.1 * 0.05 ** 0.01 *** 0.01) nogaps


**regression analysis with standard errors (appendix c)
eststo clear
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust [pweight=total_weight]
eststo model1
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust akp[pweight=total_weight]
eststo model2
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust chp[pweight=total_weight]
eststo model3
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust mhp[pweight=total_weight]
eststo model4
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust hdp[pweight=total_weight]
eststo model5
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat [pweight=total_weight]
eststo model6
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat akp [pweight=total_weight]
eststo model7
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat chp [pweight=total_weight]
eststo model8
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat mhp [pweight=total_weight]
eststo model9
reg populism1 nostalgia1 income1 female metropol education1 age agesq religious alevi1 kurdish eusup trust lifsat demsat econsat hdp [pweight=total_weight]
eststo model10
esttab model1 model2 model3 model4 model5 model6 model7 model8 model9 model10 using sepopdv.rtf, se r2 star(+ 0.1 * 0.05 ** 0.01 *** 0.01) nogaps


**note for replication

*generating nostalgia and populism index

gen populism = s105 + s108 + s118 + s119
gen populism1 = (populism-4)*6.25
gen nostalgia = s138 + s141 + s142 + s143
gen nostalgia1 = (nostalgia-4)*6.25